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Cross-session long-term memory for the DeepSeek Harness: a two-phase extraction/consolidation pipeline over a file-based memory workspace, recall injection, a citation feedback loop, lease-based job semantics, plus a settings page, a sidebar status panel

Screenshot-review skill for DeepSeek Harness: the agent opens a frontend page, screenshots it, views the screenshot itself, revises the code, then re-screenshots — iterating until the page visually matches the user's requirements. Ships as a dsh.bundle, so it installs with `dsh plugin add`.

Context curation for DeepSeek Harness: content-aware tool-output slimming, dead-log sweep, pinned user requirements and in-flight work, archive-then-compact with an audit trail.

Built-in Obsidian-style knowledge base for DSH: agents distill conversations, documents and web sources into a structured .wiki graph, with retrieval, graph export, note editing, incremental builds and multi-vault management.

DSH Web 任务面板插件：把需求、队列、子 agent 执行、自动复核、验收返工和定时执行做成一个可视化闭环。

Local semantic index over workspace documents (MD/PDF/DOCX/TXT): FTS5 BM25 + local embedding hybrid retrieval, hit citations with line numbers, and incremental updates.

Mnemosyne memory for DeepSeek Harness: remember / recall / forget / stats / sleep tools, embedded skill, auto-setup, optional auto-sync/prefetch, and a Settings panel. Data lives under ~/.dsh/mnemosyne.

DSH 智能上下文压缩插件 —— 在有限窗口内管理认知资源，让 Agent 记住真正重要的信息。 Smart context compression for DSH — managing cognitive resources within limited windows, so your Agent remembers what truly matters.

Requirement-driven dsh plugin discovery and environment recipes: plugin_guide matches natural-language needs to a curated plugin directory with reasons and install commands; recipe installs whole setups (通知全家桶, 安全审计套装...) from bundled community bundles with ordered plans.

Cross-session event-cue memory for DeepSeek Harness: auto-extracts task/conversation cues and user language habits from every turn into a persistent global cue bank, then re-injects remembered context on topic-switch detection (keyword or vector matching).

DSH용 증분 diff 리뷰어: 배치를 승인한 후 체크포인트 이후 새 변경 사항만 표시되며, Web 리뷰 패널과 `/review` 명령이 피드백을 에이전트에 다시 주입합니다.

Cross-session memory for your dsh agent: remembered, recalled, and re-verified instead of assumed.

A continuation of simon300000/dsh-auto: the Auto Approve permission preset for the DSH Web UI reviews each approval with one single-shot model call instead of a reviewer subagent, auto-approves only the actions that pass and hands the rest to human approval, and remembers confirmed decisions as project- and global-scope allow/deny lists, with an approval timeline in the right sidebar.

Local file recall: indexes the folders you choose into one local SQLite database, so 'where did I put that file?' is one query instead of a disk walk. Caches, VCS and program folders are pruned per directory; each folder keeps its own incremental anchor, so a folder added later is backfilled in full. Read-only: it never modifies, moves or deletes your files.

DSH (DeepSeek Harness) Web GUI plugin: global model token usage stats as a dedicated "Token 用量" page in Settings — incremental session-file scanning with a persistent fold cache, date-range picker with presets, model/provider filters, per-day and per-mode

Visual web settings panel for the official @tencent-connect/dsh-qqbot plugin: manage the QQ Bot AppID/AppSecret, c2c & group access modes/allowlists, cwd and requireMention directly in the DSH web settings page (reads/writes the qqbot profile's cordis.pat

A DSH plugin that automates shipping a local project: create a GitHub repository and publish it (git init/commit/push + topics + tag + release), sync requirements/progress to Linear, publish to npm, and announce in the community Discussions — to join the

Keeps an unfinished task list visible across turns. DSH clears the todos projection at the start of every turn and expects the model to rewrite the whole list, so when a turn is interrupted the plan is durably in the session log but permanently gone from the UI — and todo_write is write-only, so neither the user nor the model can read it back. This plugin registers one ordinary session/event listener, remembers the last list per session, and when a turn/start arrives whose remembered list still has unfinished work, re-appends that list so the projection stops reporting an empty plan. No fork of tool-todo and no waterfall: a plugin cannot replace the projection (the registry throws on a stateVersion mismatch), so appending the event the fold reacts to is the reachable seam. Deliberately narrow — only unfinished lists, at most one event per turn start, fails open. Verified by a controlled A/B on real sessions: identical runs differing only in whether the plugin was installed, folded through the real projection definition. Zero dependencies.

Unit conversion as a `convert` tool: 10 categories (length, area, volume, time, angle, speed, temperature, pressure, energy/heat, power) and 82 units with English and Chinese aliases, plus a locale-aware Unit Converter tab in the DSH web view with one module per category and a temperature-difference (Δ) switch.

Per-wallpaper offset for dsh-dream-skin - nudge the current wallpaper along X and Y in pixels from Settings, remembered separately for each image, URL or gradient.

Session model selector with search: two-stage loose matching (normalised substring first, subsequence as fallback, so glm53 finds GLM-5.3 and ds finds DeepSeek), providers with recent successful calls pinned first, and a reasoning-effort pane that remembers each model's last explicitly chosen effort.

Injects your own saved context entries as a Remember row after each user message, per turn or once per session, with a Settings editor and a manager page.

Local token usage and cost dashboard for DeepSeek Harness: four-segment token breakdown (miss/cache-hit/cache-write/output), cache savings estimate against the miss/hit price gap, per-session drill-down with context-growth curves and anomaly flags, global filters with shareable URLs, monthly budget progress with month-end projection, and day/month aggregate fast-path queries (O(days)) with incremental rescan.

A /remember command that writes facts into the AGENTS.md instruction hierarchy dsh already loads, plus a Memory tab showing which instructions the loader kept within its byte budget.